Unobtrusive Sleep Physiological Monitoring and Enhancement Technologies

不引人注目的睡眠生理监测和增强技术

• 批准号: RGPIN-2021-03924
• 负责人: Forouzanfar, Mohamad
• 金额: $ 2.77万
• 依托单位: École de technologie supérieure
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=753925
• 关键词: Unobtrusive; Sleep; Physiological; Monitoring; Enhancement

Sleep disorders and their accompanying health problems are among important health issues in Canada, and there is a need to develop improved technologies to objectively evaluate sleep, manage sleep, and monitor health status during sleep. Irregular sleep patterns have been linked to a higher risk of neurodegenerative disorders, cardiovascular disease, and cancer. Sleep problems affect one-in-two Canadian adults and their prevalence is higher in women and increases with age. In addition to its critical role in well-being and quality of life, sleep provides a unique baseline window into human body function at rest that can help characterize health and disease patterns. For example, it has been found that blood pressure and heartrate profiles during sleep are strongly associated with deaths, cardiovascular events, and progressive loss of renal function, independently of their daytime profiles. Moreover, many health-related events, such as stroke, may occur during sleep while we are unconscious leading to late diagnosis and treatment. While there exists medicine, supplements, and meditation therapies to improve sleep disorders, there has been little technological effort to improve and manage sleep and to monitor sleep physiology and health. The operation of most current physiological monitors relies on active interaction with user/expert, continuous usage of such monitors can be disturbing and disruptive to sleep, and the analysis of recorded data requires expert interpretation. There is a need for portable, unobtrusive, and inexpensive technologies that can continuously monitor and enhance sleep in real-world environments such as the home. The main goals of the proposed research are the design and development of 1) smart and unobtrusive intervention technologies for sleep enhancement and management, 2) automatic algorithms to aid in the analysis and interpretation of physiological data, overcome the intrinsic limitations of human perception and bias, estimate important physiological parameters, and detect and predict health-related issues, and 3) wearable and contactless technologies for continuous in-sleep physiological measurement without disturbing sleep. The proposed research program is expected to have a significant impact in the field of Biomedical Engineering and on Sleep Technologies. Novel techniques for unobtrusive physiological monitoring and sleep enhancement will be developed, including new wearable and contactless sensors, signal processing methods, and machine learning algorithms. The developed technologies are expected to have significant impact on quality of life of Canadians, particularly those affected by sleep problems, such as women and the elderly. Moreover, Doctoral and Master's students will be trained in interdisciplinary and collaborative research involving human subjects, and so will develop skills of value to the Canadian biomedical and wearable devices industries, the sleep research community, and healthcare.

睡眠障碍及其伴随的健康问题是加拿大重要的健康问题之一，需要开发改进的技术来客观评估睡眠、管理睡眠和监测睡眠期间的健康状况。不规则的睡眠模式与神经退行性疾病、心血管疾病和癌症的较高风险有关。睡眠问题影响着二分之一的加拿大成年人，女性的患病率更高，并且随着年龄的增长而增加。睡眠除了在福祉和生活质量方面发挥着关键作用外，还为了解人体休息时的功能提供了一个独特的基线窗口，有助于表征健康和疾病模式。例如，已经发现睡眠期间的血压和心率曲线与死亡、心血管事件和肾功能逐渐丧失密切相关，与白天的曲线无关。此外，许多与健康相关的事件，例如中风，可能在我们失去意识的睡眠期间发生，导致诊断和治疗较晚。尽管存在改善睡眠障碍的药物、补充剂和冥想疗法，但在改善和管理睡眠以及监测睡眠生理和健康方面几乎没有做出任何技术努力。 大多数当前生理监测器的操作依赖于与用户/专家的主动交互，连续使用此类监测器可能会干扰和破坏睡眠，并且记录数据的分析需要专家解释。人们需要一种便携式、不显眼且廉价的技术，能够持续监测和增强家庭等现实环境中的睡眠。拟议研究的主要目标是设计和开发1）用于睡眠增强和管理的智能且不显眼的干预技术，2）自动算法以帮助分析和解释生理数据，克服人类感知和偏见的内在局限性，估计重要的生理参数，并检测和预测与健康相关的问题，以及3）用于连续睡眠生理的可穿戴和非接触式技术 测量时不影响睡眠。拟议的研究计划预计将对生物医学工程和睡眠技术领域产生重大影响。将开发用于不引人注目的生理监测和睡眠增强的新技术，包括新的可穿戴和非接触式传感器、信号处理方法和机器学习算法。所开发的技术预计将对加拿大人的生活质量产生重大影响，特别是那些受睡眠问题影响的人，例如妇女和老年人。此外，博士生和硕士生将接受涉及人类学科的跨学科和协作研究的培训，从而培养对加拿大生物医学和可穿戴设备行业、睡眠研究界和医疗保健有价值的技能。